CVE-2022-41902 : Vulnerability Insights and Analysis

TensorFlow, an open-source machine learning platform, was found to have a critical vulnerability known as an out-of-bounds write issue in grappler. This vulnerability could lead to memory reads out of bounds or system crashes when specific conditions are met. This article provides an overview of CVE-2022-41902, its impact, technical details, and mitigation strategies.

Understanding CVE-2022-41902

TensorFlow's module, Grappler, is responsible for optimizing computation graphs. The vulnerability lies in the function MakeGrapplerFunctionItem, where improper input size handling can trigger memory corruption.

What is CVE-2022-41902?

The CVE-2022-41902 vulnerability in TensorFlow arises from the mishandling of input and output sizes in the MakeGrapplerFunctionItem function. This could result in memory read operations accessing areas beyond the allocated memory space, leading to unpredictable behavior or crashes.

The Impact of CVE-2022-41902

This vulnerability poses a high risk to systems leveraging TensorFlow for machine learning tasks. An attacker could potentially exploit this issue to execute arbitrary code, compromise data integrity, or cause denial of service.

Technical Details of CVE-2022-41902

The vulnerable function MakeGrapplerFunctionItem in TensorFlow can allow attackers to perform out-of-bounds memory reads, leading to severe consequences.

Vulnerability Description

The flaw is triggered when input sizes exceed the output sizes within the MakeGrapplerFunctionItem function, resulting in memory corruption issues.

Affected Systems and Versions

TensorFlow versions 2.8.4 to 2.10.0 are impacted by CVE-2022-41902. Specifically, versions 2.8.4, 2.9.0 to 2.9.3, and 2.10.0 to 2.10.1 are vulnerable to this out-of-bounds write flaw.

Exploitation Mechanism

By providing larger input sizes than output sizes, an attacker can trigger memory read operations beyond the intended boundaries, potentially leading to unauthorized access or system crashes.

Mitigation and Prevention

It is crucial to take immediate steps to address and prevent the exploitation of CVE-2022-41902 to secure TensorFlow environments.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to the patched versions. For TensorFlow 2.8.4, 2.9.3, and 2.10.1, the fix is available. Ensure that all TensorFlow-based applications are running on the secure versions to prevent exploitation.

Long-Term Security Practices

Implement secure coding practices, conduct regular security audits, and stay informed about TensorFlow security advisories to protect against future vulnerabilities.

Patching and Updates

GitHub commit a65411a1d69edfb16b25907ffb8f73556ce36bb7 addresses the CVE-2022-41902 vulnerability. The fix is included in TensorFlow 2.11.0, and will also be applied to TensorFlow 2.8.4, 2.9.3, and 2.10.1 to safeguard against this critical issue.